Yann Chevaleyre





I am Full Professor in computer science at Dauphine PSL, researcher in Artificial Intelligence. I’m currently co-head of the Math and Computer Science departement at Dauphine university, as well as head of Dauphine’s master in Computer Science.




Research Interests

• Machine Learning
• Reinforcement Learning and Imitation in Robotics
• Multiagent Systems and Computational Social Choice

Current Teaching Activities

• Fundamentals of Machine Learning, M2 IASD
• Introduction to Machine Learning, M1 I2D

Short Bio

• 2017 : Full professor at LAMSADE, university of Paris Dauphine
• 2010 : Full professor at LIPN, head of the machine learning team
• 2002 : Assistant Professor at LAMSADE.
• 2001 : PhD in machine learning at LIP6

A Few Recent Publications

• A. Araujo, B. Negrevergne, Y. Chevaleyre, J. Atif, On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory, 35th Conference on Artificial Intelligence (AAAI 2021)
• R. Pinot, R. Ettedgui, G. Rizk, Y. Chevaleyre, J. Atif, Randomization matters How to defend against strong adversarial attacks, International Conference on Machine Learning (ICML 2020).
• L. Meunier, Y. Chevaleyre, J. Rapin, C. Royer, O. Teytaud, On Averaging the Best Samples in Evolutionary Computation. (PPSN 2020). pp.661-674
• A. Duburcq, Y. Chevaleyre, N. Bredeche, G. Boéris, Online trajectory planning through combined trajectory optimization and function approximation: Application to the exoskeleton Atalante. IEEE International Conference on Robotics and Automation (ICRA 2020), 3756-3762. Nominated for the Best Paper Award in Service Robotics.
• Alexandre Araujo, Benjamin Negrevergne, Yann Chevaleyre and Jamal Atif. Understanding and Training Deep Diagonal Circulant Neural Networks 24th European Conference on Artificial Intelligence (ECAI 2020)
• K. Belahcene, N. Sokolovska, Y. Chevaleyre, J.-D. Zucker. Learning Interpretable Models using Soft Integrity Constraints, ACML 2020.
• M. Clertant, N. Sokolovska, Y. Chevaleyre, B. Hanczar, Interpretable Cascade Classifiers with Abstention (AISTATS 2019)

For more Publications, see google scholar or DBLP

Current PhD supervision

• Geovani Rizk, working on Graphical Bandits, co-supervised with Rida Laraki. (CIFRE with Huawei)
• Alexandre Vérine, working on Invertible Neural Networks and Adversarial Attacks, co-supervised with Benjamin Negrevergne and Fabrice Rossi
• Alexandre Araujo, working on Leveraging Toeplitz Matrix Properties to Analyse and Improve Deep Neural Networks, co-supervised with Benjamin Negrevergne and Jamal Atif
• Alexis Duburcq, working on Machine Learning and Reinforcement Learning for Exoskeleton trajectory optimization. (CIFRE with WanderCraft).

Contact Information

• e-mail: yann.chevaleyre (at) dauphine.fr
• postal address: Université Dauphine - PSL, Laboratoire LAMSADE, Place du Maréchal de Lattre de Tassigny, 75 775 Paris Cedex 16, France.